Can you diagnose STEMI on a rhythm strip?
Paramedic Humphrey has just responded to the residence of a lovely 72-year old woman who fell in her home. As he engages her in conversation, he makes a point of asking whether she “tripped”, or whether she had any preceding symptoms that may have induced her fall. She responds, “I don’t think I had any symptoms.”
Humphrey is not convinced that he wants to do a 12-lead EKG on this patient, as he is fairly confident that this is a mechanical fall, so he decides to compromise and take a quick look with the rhythm strip (“monitor mode”) along with his vital signs. He sees the following strip on his monitor:

As his eyes widen, he hands the strip to his partner and taps excitedly on the paper. “S-T-E-M-I,” he mouths.
The rhythm strip is pretty convincing. Is it sufficient for diagnosis?
It should not be surprising to read that the heart has an electrical conduction system to provide synchronicity to muscle contraction. Likewise, it should not be surprising to read that the purpose of the EKG is to detect this electrical activity and translate it into a time vs. amplitude chart. With these assumptions, we can approach the manner in which the machine makes this conversion.
Electricity, in general, is propagated through any material that permits the flow of electrons, inclusive of the human body. Thus, when the heart’s conduction system fires, some component of that current continues to flow throughout the body. The exact amount of detectable electricity at the level of the skin depends on impedance, which differs to some extent between people. The signal seen at the skin surface is very high in noise, and very low in voltage, which necessitates some processing to become a readable signal. The exact components used to accomplish this, as well as the sequence in which it is done, depend on the particular machine and software. Regardless of this sequence, several steps must occur.
During the initial acquisition of information at the electrode, amplification must occur. During amplification, the low voltages at the skin are received and increased by the machine to become more readable (“turning up the volume”).
The resulting waveform continues to include noise from multiple sources. These include 50/60Hz oscillations from the power lines, noise from other muscles contracting (5-50Hz), isoline drift from patient movement and respirations (0.12-0.5Hz), and more [2].

This is the point at which signal filtering occurs. As we’ll see, this process can significantly impact accurate ST segment interpretation.
In order to help remove extraneous noise, the system passes the signal through several filters, which remove data above and below certain frequency thresholds [1].

High-Pass Filtering:
Baseline wander (the appearance of an EKG line ‘roaming’ up and down the strip instead of laying flat) is a low-frequency component present in the ECG strip that is handled by passing the data through a high-pass filter. This type of filter allows frequencies above a certain threshold to pass (“high frequencies may pass”). The goal is to select a frequency that is just high enough to help cut out some of that low-frequency baseline movement without otherwise removing important features of the EKG. Think of this as a dam built in a river, which allows water at the top of the water column to flow over it, while blocking water at the bottom.
Low-Pass Filtering:
On the other end of the spectrum, high-frequency noise, which makes the EKG line appear ‘shaky’ is removed with a low-pass filter (“low frequencies may pass”). Think of this like a lawnmower, which chops off everything over a certain level, and allows grass up to a certain height to remain.
The difference in frequency between the high pass and low pass filters is referred to as the bandwidth, and this determines the frequency response indicated on the EKG strip.
Thus, lowering the high-pass filter will allow more baseline drift and low-frequency artifact from patient movement and respiration. Raising the low-pass filter will allow for more high-frequency artifact. When bouncing around the back of a noisy vehicle, or when dealing with a shivering patient, the low-pass filter allows the strip to appear much cleaner by removing this noise.
If the filters can be adjusted to remove noise, why can’t we set the bandwidth to be very narrow in order to exclude the most possible noise? In theory, this would provide the ‘cleanest’ strip.
The problem with this approach is that different parts of the EKG strip are most accurately represented at different frequencies. Of particular interest to us is the ST segment, which is a relatively low-frequency component of the EKG.
This is the point at which a rhythm strip becomes inferior to a true 12-lead EKG.
With a rhythm strip (“monitor mode”), most machines will utilize a more narrow bandwidth in order to optimize readability and strip quality. While this permits quick rhythm interpretation, it can distort important parts of the EKG strip, including the ST segment.
The following image displays an EKG waveform before and after the application of a 1Hz high-pass filter [3].

It is apparent that there is significant difference between the two waveforms, particularly with respect to the ST segment and T wave.
If the bandwidth is opened by dropping the high-pass filter to 0.5Hz, this distortion is minimized [3].

To emphasize this point, I performed an EKG on myself using both a “monitor” mode (smaller frequency response; 1-30Hz) and a “diagnostic” mode (larger frequency response; 0.5-40Hz). Despite being performed in immediate succession with identical lead placement, the frequency response alone was sufficient to cause measurable ST changes. The difference in frequency response is noted in the bottom-left corner of the EKGs.

Here is another striking example of major ST segment differences between the “monitor” mode and the “diagnostic” mode on a patient with a pacemaker.

Usually, the frequency response on EKG monitors can be configured in their settings. In the manual for the monitors used by my fire department, the following options were offered [10]:

Clearly, the low frequencies are important for ST segment interpretation.
How about the high frequencies?
In an ideal setting, we would use the widest bandwidth to permit the most accurate EKG. However, the prehospital world is rarely ideal. The fact that this monitor offers a diagnostic mode with a low-pass filter at 40Hz suggests that some consideration was placed into creating an option that offered a reasonable amount of artifact reduction. In the back of a running ambulance, this may help significantly with reducing unnecessary artifact. As long as the high-pass filter is set low enough to permit accurate ST segment interpretation, we may find the omission of high-frequency components to be complimentary to the nature of our work. This determination will likely need to be made at the individual agency level.
In conclusion, the ST segment cannot be accurately interpreted in a standard rhythm strip (“monitor mode”), by virtue of its narrow bandwidth.
- Bharadwaj A and Kamath U (February 14th, 2011). Techniques for accurate ECG signal processing [Web log post]. Retrieved from http://www.eetimes.com/document.asp?doc_id=1278571.
- Lugovaya T.S. Biometric human identification based on electrocardiogram. [Master’s thesis] Faculty of Computing Technologies and Informatics, Electrotechnical University “LETI”, Saint-Petersburg, Russian Federation; June 2005.
- Buendia-Fuentes F, et al. High-Bandpass Filters in Electrocardiography: Source of Error in the Interpretation of the ST Segment. ISRN Cardiology 2012.
- Gregg RE et al. What is inside the electrocardiograph? J Electrocardiol 2008;41(1):8-14.
- Bragg-Remschel DA et al. Frequency response characteristics of ambulatory ECG monitoring systems and their implications for ST segment analysis. Am Heart J 1982;103(1):20-31.
- Tayler DI and Vincent R. Artefactual ST segment abnormalities due to electrocardiograph design. Br Heart J 1985;54(2):121-128.
- Burri H et al. Simulation of anteroseptal myocardial infarction by electrocardiographic filters. J Electrocardiol 2006;39(3):253-258.
- Bailey JJ et al. Recommendations for standardization and specifications in automated electrocardiography: bandwidth and digital signal processing. A report for health professionals by an ad hoc Writing Group of the Committee on electrocardiography and Cardiac Electrophysiology of the Council on Clinical Cardiology, American Heart Association. Circulation 1990;81(2):730–739.
- Kligfield P and Okin PM. Prevalence and clinical implications of improper filter settings in routine electrocardiography. American Journal of Cardiology 2007;99(5):711–713.
- LIFEPAK 15 Monitor/Defibrillator Setup Options. Physio Control 2008.